Compositions and methods for immunodominant antigens of Mycobacterium tuberculosis

ABSTRACT

Contemplated compositions, devices, and methods are drawn to various antigens from the pathogen  M. tuberculosis  and their use in vaccines, therapeutic agents, and various diagnostic tests. In particularly preferred aspects, the antigens are immunodominant and have quantified and known relative reactivities with respect to sera of a population infected with the pathogen, and/or have a known association with a disease parameter.

This application is a divisional of U.S. application Ser. No. 12/465,136 filed May 13, 2009, now issued U.S. Pat. No. 7,927,818 which is continuation-in-part of our U.S. application Ser. No. 12/447,620 filed Dec. 3, 2009, which is a U.S. national phase filing of International Application No. PCT/US07/23299, which was filed Nov. 1, 2007 which claims priority to U.S. Provisional Application No. 60/856,217, which was filed Nov. 1, 2006, all of which are incorporated by reference herein in their entirety.

FIELD OF THE INVENTION

The field of the invention is compositions and methods related to selected antigens from Mycobacterium tuberculosis, especially as they relate to their use in diagnostic and therapeutic compositions and methods.

BACKGROUND

Antigens for vaccination and/or diagnostic purposes are typically single antigens from a pathogen, or complex mixtures of multiple known antigens from a pathogen, or of multiple known and unknown antigens of a pathogen such as live, attenuated or inactivated bacteria or viruses. Depending on the particular type of pathogen, single antigens may provide a quantifiable signal in immunodiagnostic tests (antibody or cellular responses). However, due to variations among individuals in their immune response profiles, single antigen tests are often not sufficient to obtain useful diagnostic information with useful specificity and sensitivity.

For example, multiple tests are often required for accurate diagnosis of tuberculosis (TB). Most typically, a person suspected of being infected with M. tuberculosis is tested using the tuberculin skin test (TST) that often provides variable results, which make their interpretation rarely consistent. Alternative tests are the interferon gamma release assays (IGRAs). These tests are more specific that TST but they still do not provide means of distinguishing persons having active tuberculosis from persons who are infected but are not currently harboring an active disease process. For investigation of active TB, a sputum smear test for acid fast bacilli can be employed to identify M. tuberculosis directly, which tends to provide good specificity. However, the sensitivity varies widely among different laboratories. To obtain a more definite result, active TB may be diagnosed by bacterial culture from, e.g., sputum or other bodily fluids. Unfortunately, such test requires a dedicated microbiology laboratory and several weeks to obtain the results. More recently developed methods, such as real time PCR assays are relatively accurate but require sophisticated equipment and highly trained personnel, and they are very susceptible to cross-sample contamination.

Based on the above drawbacks it is therefore desirable to develop an antibody-based test that would overcome at least some of the difficulties associated with bacterial culture, genetic analysis or other known methods, and considerable effort has been spent defining and identifying immunoreactive proteins in membrane fractions of M. tuberculosis and M. tuberculosis-conditioned culture medium (culture filtrate proteins' or CFPs). Candidate antigens are typically tested for diagnostic utility in ELISAs and Western blots using TB sera and sera from healthy controls. CFPs are more widely studied because of the convenience of working with soluble proteins. Of the >100 M. tuberculosis proteins in culture filtrates (representing about 2.5% of the M. tuberculosis proteome), roughly two dozen are recognized by sera from TB patients, most of which have been previously identified. Yet despite these efforts, there remains no effective serological test with the sensitivity and specificity required to accurately diagnose TB, particularly in the early stage of infection. Moreover, none of the heretofore known antigens is generally applicable to differentiate among stages (e.g., active disease versus non-active), secondary infections, etc., as the signal is either impossible to deconvolute (e.g., compound signal from inactivated pathogen) or only provides a single data point.

Similarly, where known antigens are used in a vaccine, numerous problems are known due to the variability of individual immune response and potential prior exposure. More recently, multivalent vaccine preparations have become available where in a single dose, multiple and distinct antigens, from multiple and distinct serotypes, of a single pathogenic organisms were combined (Prevnar™: Heptavalent vaccine against Streptococcus pneumoniae capsular serotypes 4, 6B, 9V, 14, 18C, 19F, and 23F). While such mixed preparations tend to provide a broader range of protection against different serotypes, various difficulties nevertheless remain. Most significantly, where a single antigen fails to elicit an immune response, coverage to the corresponding serotype is not present. Thus, combination of single defined antigens from several serotypes merely combines benefits and problems associated with the single antigens.

Therefore, while numerous methods of identification and use of antigens are known in the art, all or almost all of them suffer from one or more disadvantages. Consequently, there remains a large, unmet need to provide improved compositions and methods of antigens from M. tuberculosis for diagnosis and therapy of TB.

SUMMARY OF THE INVENTION

The present invention is directed to immunodominant antigens from M. tuberculosis wherein the antigens are known to react, that is, have known reactivities (and particularly known relative reactivities) to serum of a population of patients infected with the pathogen. Thus, the antigens presented herein will have a statistically high probability to elicit an immune response in a relatively large group of patients. Further, where the antigens are determined from selected sub-populations (e.g., active stage, latent stage, past infection, prior vaccination, not infected, co-infection with other pathogen, etc.), the antigens may also have a known association with a disease parameter.

In aspect of the inventive subject matter, an antigen composition comprises a plurality of antigens of M. tuberculosis encoded by nucleic acids selected from the group consisting of SEQ ID NO:1 to SEQ ID NO:586 (or any subgroup of such sequences), or fragments thereof, wherein at least two of the antigens elicit an immune response.

In other contemplated aspects of the inventive subject matter, an antigen composition comprises two or more immunodominant antigens of a pathogenic organism and are associated with a carrier, wherein the antigens have quantified and known relative reactivities with respect to sera of a population infected with the organism, and wherein the antigens have a known association with a disease parameter. Most preferably, immunodominant antigens are polypeptides and are encoded by nucleic acids having a sequence according to SEQ ID NO:1 to SEQ ID NO:586 (or comprise fragments thereof).

It is further contemplated that the known reactivities may be characterized by a variety of factors, however, it is particularly preferred that the known reactivities are characterized by strength of immunogenicity and/or time course of the infection. It is generally preferred that the parameter is activity state of the disease, a previous exposure to the pathogen, the duration of exposure to the pathogen, a chronic infection, past disease, active infection, inactive infection, at least partial immunity to infection with the pathogen, and/or outcome upon treatment.

In another aspect of the inventive subject matter, the carrier is a pharmaceutically acceptable carrier, and the composition is formulated as a vaccine. In such aspects, it is generally preferred that the vaccine comprises multiple (e.g., at least two, four, or six) antigens. It is still further contemplated that the antigens or fragments thereof are at least partially purified and/or recombinant.

In further contemplated aspects, the carrier may also be a solid carrier, and the plurality of antigens is disposed on the carrier either as a mixture or as an array. In such arrays, it is generally preferred that the antigens have at least two distinct known reactivities and/or parameters. It is also contemplated that the antigens or fragments thereof may be in crude expression extracts, in partially purified form (e.g., purity of less than 60%), or in highly purified form (e.g., purity of at least 95%). The antigens in such arrays may be recombinant or native. Alternatively, solid phases need not be limited to planar arrays, but may also include beads, columns, dipstick-type formats, etc.

Aspects of this invention include diagnostic assay utilizing at least two immunodominant antigens of M. tuberculosis. Antibody assays comprise contacting a sample of bodily fluid that contains antibodies against M. tuberculosis, for example, serum, with at least two immunodominant antigens of this invention and detecting antigen-antibody binding by any satisfactory method, preferably by formation of a color or generation of a fluorescent signal. For example, antigens immobilized on a solid surface, either individually in discrete areas or in a mixture, may be used to immobilize antibodies from the sample, and an anti-antibody linked directly or indirectly to a color-forming enzyme may then be added for signal generation in the standard ELISA format. Alternatively, fluorescence signals may be generated by methods such as linking (directly or indirectly) an anti-antibody to a fluorescence-emitting substance. Aspects of this invention also include use of at least two immunodominant antigens free in solution rather than immobilized on a surface. For example, a sample of peripheral blood, a bodily fluid containing T-lymphocytes, may be contacted with such antigens in vitro. Reactions between T-lymphocytes and antigen (on an antigen-presenting cell) are, like antigen-antibody reactions, epitope-specific even though T-lymphocytes and antibodies may recognize different epitopes. If the antigens are recognized, the T-lymphocytes produce at least one cytokine, such as interferon gamma, which is then detected by a (directly or indirectly) labeled antibody. Aspects of this invention further include kits of reagents for performing assays. Such kits include at least two immunodominant antigens according to this invention.

Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF THE DRAWING

FIGS. 1A and 1B depict exemplary microarrays probed with sera from TB-positive and LTBI-negative (i.e., not infected with M. tuberculosis) individuals, respectively.

FIGS. 2A and 2B are graphs depicting exemplary statistical representations in differences in signals for TB-positive and LTBI-negative results.

FIG. 2C is a table listing selected TB antigens using one preferred exemplary ranking algorithm.

FIGS. 3A and 3B depict exemplary fluorimetric and colorimetric visualization of exemplary microarrays and respective scatter plots indicating the correlation between the visualizations.

FIGS. 4A and 4B depict the proteins ranking in random forests, CERNO, and random forests with CERNO-prefiltered data.

FIG. 5 depicts a protein which exhibits a tail distribution of higher intensity signals in TB samples that is not seen in non-TB samples.

DETAILED DESCRIPTION

The inventors have discovered various immunodominant antigens from M. tuberculosis that are suitable for diagnostic and therapeutic purposes. Particularly preferred immunodominant antigens and are those encoded by nucleic acids having a sequence according to SEQ ID NO:1 to SEQ ID NO:586, and it is generally contemplated that such antigens can be used as single antigens, or in combination (optionally also in combination with antigens from another pathogen) in the manufacture of various diagnostic devices, therapeutic compositions, and vaccines. Preferably, the immunodominant antigens suitable for diagnostic and therapeutic purposes are encoded by the sequences designated Rv0798c (SEQ ID NO:121), Rv1886c (SEQ ID NO:270), Rv2031c (SEQ ID NO:284), Rv3616c (SEQ ID NO:509), Rv3804c (SEQ ID NO:534), Rv3874 (SEQ ID NO:547), Rv0302 (SEQ ID NO:52), Rv0379 (SEQ ID NO:65), Rv0394c (SEQ ID NO:66), Rv0456c (SEQ ID NO:74), Rv0632c (SEQ ID NO:103), Rv0944 (SEQ ID NO:142), Rv0984(SEQ ID NO:146), Rv1030 (SEQ ID NO:153), Rv1196 (SEQ ID NO:174), Rv1242 (SEQ ID NO:180), Rv1284 (SEQ ID NO:187), Rv1387 (SEQ ID NO:206), Rv1837c (SEQ ID NO:264), Rv1926c (SEQ ID NO:275), Rv1980c (SEQ ID NO:281), Rv2094c (SEQ ID NO:294), Rv2544 (SEQ ID NO:363), Rv2618 (SEQ ID NO:375), Rv2746c (SEQ ID NO:391), Rv2870c (SEQ ID NO:407), Rv2873 (SEQ ID NO:408), Rv2875 (SEQ ID NO:409), Rv3050c (SEQ ID NO:434), Rv3248c (SEQ ID NO:458), Rv3376 (SEQ ID NO:478), Rv3763 (SEQ ID NO:527), Rv3810 (SEQ ID NO:536), Rv3864 (SEQ ID NO:545), Rv2252 (SEQ ID NO:323), Rv2282c (SEQ ID NO:569), Rv0212c (SEQ ID NO:557), Rv3243c (SEQ ID NO:456), Rv3675 (SEQ ID NO:519), Rv2984 (SEQ ID NO:423), Rv1175c (SEQ ID NO:169), Rv3326 (SEQ ID NO:578), Rv3628 (SEQ ID NO:513), Rv3775 (SEQ ID NO:584), Rv3362c (SEQ ID NO:475), Rv0801 (SEQ ID NO:122), Rv1629 (SEQ ID NO:566), Rv0272c (SEQ ID NO:558), Rv3762c (SEQ ID NO:583), Rv3319 (SEQ ID NO:577), Rv3495c (SEQ ID NO:581), Rv2151c (SEQ ID NO:308), Rv0227c(SEQ ID NO:37), Rv0280(SEQ ID NO:50), Rv0993 (SEQ ID NO:148), Rv1306 (SEQ ID NO:192), Rv1363c (SEQ ID NO:204), Rv2050 (SEQ ID NO:288), Rv2116 (SEQ ID NO:299), Rv3417c (SEQ ID NO:486), Rv3653 (SEQ ID NO:516), Rv1253 (SEQ ID NO:182), Rv3413c (SEQ ID NO:485), Rv1635c (SEQ ID NO:232), Rv3021c (SEQ ID NO:432), Rv1193 (SEQ ID NO:173), Rv2592c (SEQ ID NO:369), Rv3620c (SEQ ID NO:510), Rv0929 (SEQ ID NO:139), Rv0959 (SEQ ID NO:145), Rv1162 (SEQ ID NO:166), Rv2389c (SEQ ID NO:341), Rv2984 (SEQ ID NO:423), Rv2588c (SEQ ID NO:367), Rv0171 (SEQ ID NO:26), Rv1865c (SEQ ID NO:267), Rv2074 (SEQ ID NO:290), Rv0543c (SEQ ID NO:87), Rv1677 (SEQ ID NO:237), Rv1304 (SEQ ID NO:191), Rv2841c (SEQ ID NO:400), Rv3680 (SEQ ID NO:520), Rv0831c (SEQ ID NO:125), Rv2032 (SEQ ID NO:285), Rv3127 (SEQ ID NO:446), Rv3272 (SEQ ID NO:464), Rv3323c (SEQ ID NO:470), Rv3508 (SEQ ID NO:494), Rv3628 (SEQ ID NO:513), Rv1173 (SEQ ID NO:167), Rv2623 (SEQ ID NO:376), Rv0527 (SEQ ID NO:85), Rv1620c (SEQ ID NO:229), Rv1901 (SEQ ID NO:272), Rv2151c (SEQ ID NO:308), Rv0362 (SEQ ID NO:60), Rv3129 (SEQ ID NO:447), Rv3140 (SEQ ID NO:449), Rv0340 (SEQ ID NO:56), Rv2792c (SEQ ID NO:395), Rv3003c (SEQ ID NO:426), Rv3019c (SEQ ID NO:431), Rv3862c (SEQ ID NO:544), Rv0572c (SEQ ID NO:91), Rv2477c (SEQ ID NO:356), Rv2659c (SEQ ID NO:379), Rv0311 (SEQ ID NO:54), Rv0350 (SEQ ID NO:57), Rv2127 (SEQ ID NO:301), Rv3875 (SEQ ID NO:548), Rv0877 (SEQ ID NO:134), Rv1916 (SEQ ID NO:274), Rv2138 (SEQ ID NO:303), Rv2847c (SEQ ID NO:403), Rv3118 (SEQ ID NO:444), Rv2495c (SEQ ID NO:358), Rv3669 (SEQ ID NO:517), Rv0281 (SEQ ID NO:51), Rv2711 (SEQ ID NO:383), Rv2744c (SEQ ID NO:390), Rv3803c (SEQ ID NO:533), Rv1239c (SEQ ID NO:179), Rv2147c (SEQ ID NO:307), Rv2253 (SEQ ID NO:324), Rv0308 (SEQ ID NO:53), Rv0587 (SEQ ID NO:95), Rv1564c (SEQ ID NO:224), Rv2185c (SEQ ID NO:313), Rv1805c (SEQ ID NO:261), Rv2729c (SEQ ID NO:386), Rv3386 (SEQ ID NO:481), Rv3515c (SEQ ID NO:497), Rv0772 (SEQ ID NO:116), Rv2948c (SEQ ID NO:420), Rv0006 (SEQ ID NO:1), Rv1906c (SEQ ID NO:273), Rv2244 (SEQ ID NO:322), Rv2468c (SEQ ID NO:354), Rv3701c (SEQ ID NO:522), Rv0054 (SEQ ID NO:6), Rv1945 (SEQ ID NO:277), Rv3345c (SEQ ID NO:472), Rv0276 (SEQ ID NO:48), Rv0709 (SEQ ID NO:108), Rv1527c (SEQ ID NO:220), Rv2048c (SEQ ID NO:287), Rv2414c (SEQ ID NO:345), Rv3524 (SEQ ID NO:499), Rv3556c (SEQ ID NO:502), Rv1322 (SEQ ID NO:196), Rv2934 (SEQ ID NO:417), Rv0270 (SEQ ID NO:47), Rv0612 (SEQ ID NO:99), Rv1699 (SEQ ID NO:242), Rv2728c (SEQ ID NO:385), Rv3017c (SEQ ID NO:430), Rv3364c (SEQ ID NO:476), Rv3418c (SEQ ID NO:487), Rv3718c (SEQ ID NO:525), Rv0426c (SEQ ID NO:70), Rv1181 (SEQ ID NO:171), Rv1725c (SEQ ID NO:250), Rv0256c (SEQ ID NO:44), Rv0605 (SEQ ID NO:98), Rv0737 (SEQ ID NO:114), Rv0834c (SEQ ID NO:126), Rv1255c (SEQ ID NO:184), Rv2224c (SEQ ID NO:320), Rv1843c (SEQ ID NO:265), Rv2333c (SEQ ID NO:334), Rv2490c (SEQ ID NO:357), Rv3183 (SEQ ID NO:454), Rv0668 (SEQ ID NO:106), Rv1556 (SEQ ID NO:223), Rv1673c (SEQ ID NO:236), Rv3513c (SEQ ID NO:496), Rv3675 (SEQ ID NO:519), Rv3870 (SEQ ID NO:546), Rv3891c (SEQ ID NO:552), Rv0163 (SEQ ID NO:24), Rv0710 (SEQ ID NO:109), Rv1297 (SEQ ID NO:189), Rv1745c (SEQ ID NO:255), Rv0600c (SEQ ID NO:97), Rv1536 (SEQ ID NO:222), Rv1738 (SEQ ID NO:254), Rv2524c (SEQ ID NO:359), Rv3086 (SEQ ID NO:440), Rv3367 (SEQ ID NO:477), Rv0135c (SEQ ID NO:20), Rv0627 (SEQ ID NO:101), Rv1448c (SEQ ID NO:213), Rv3224a (SEQ ID NO:455), Rv0029 (SEQ ID NO:2), Rv0846c (SEQ ID NO:129), Rv1159 (SEQ ID NO:165), Rv1186c (SEQ ID NO:172), Rv1705c (SEQ ID NO:243), Rv1713 (SEQ ID NO:248), Rv2476c (SEQ ID NO:355), Rv3402c (SEQ ID NO:483), Rv2615c (SEQ ID NO:374), Rv2995c (SEQ ID NO:425), Rv3788 (SEQ ID NO:585), Rv0140 (SEQ ID NO:555), Rv0203 (SEQ ID NO:33), Rv1531 (SEQ ID NO:565), Rv1693 (SEQ ID NO:241), Rv1882c (SEQ ID NO:269), Rv2143 (SEQ ID NO:568), Rv2367c (SEQ ID NO:570), Rv0584 (SEQ ID NO:94), Rv1651c (SEQ ID NO:567), Rv3197a (SEQ ID NO:576), Rv3369 (SEQ ID NO:579), Rv3825c (SEQ ID NO:586), Rv0101 (SEQ ID NO:15), Rv0808 (SEQ ID NO:123), Rv0814c (SEQ ID NO:560), Rv2153c (SEQ ID NO:309), Rv2933 (SEQ ID NO:416), Rv0071 (SEQ ID NO:9), Rv2471 (SEQ ID NO:571), Rv2979c (SEQ ID NO:575), Rv0155 (SEQ ID NO:556), Rv0581 (SEQ ID NO:559), Rv2631 (SEQ ID NO:377), Rv3455c (SEQ ID NO:489), Rv3601c (SEQ ID NO:505), Rv0896 (SEQ ID NO:562), Rv1641 (SEQ ID NO:234), Rv3005c (SEQ ID NO:427), Rv3759c (SEQ ID NO:582), Rv3800c (SEQ ID NO:532), Rv0187 (SEQ ID NO:30), Rv2379c (SEQ ID NO:338), Rv2434c (SEQ ID NO:352), Rv2940c (SEQ ID NO:574), Rv3477 (SEQ ID NO:580), Rv0435c (SEQ ID NO:72), Rv0844c (SEQ ID NO:128), Rv0856 (SEQ ID NO:561), Rv1191 (SEQ ID NO:564), Rv2803 (SEQ ID NO:397), Rv0783c (SEQ ID NO:118), Rv1054 (SEQ ID NO:563), Rv1689 (SEQ ID NO:240), Rv2539c (SEQ ID NO:572), Rv2859c (SEQ ID NO:573), Rv3777 (SEQ ID NO:528), and fragments thereof. Most preferably, the immunodominant antigens are encoded by sequences designated Rv0798c (SEQ ID NO:121); Rv1886c (SEQ ID NO:270); Rv2031c (SEQ ID NO:284); Rv3616c (SEQ ID NO:509); Rv3804c (SEQ ID NO:534); and Rv3874 (SEQ ID NO:547).

As used herein, the term “immunodominant antigen” refers to an antigen that elicits in at least one stage of the infection production of one or more types of antibodies (e.g., IgG, IgA, IgE, IgM, etc.) in at least 20%, more typically at least 40%, and most typically at least 70% of a population exposed to the antigen, or wherein, when compared to other antigens of the same pathogen, the average binding affinity and/or average quantity of the antibodies produced in the patient in at least one stage of the disease is at least in the upper half, more typically upper tertile, and most typically upper quartile. Most typically, the average binding affinity and/or average quantity of the antibodies is reflected in the signal intensity and signal intensity can therefore be used as a surrogate marker for average binding affinity and/or average quantity of the antibodies. In further aspects, preferred immunodominant antigens are also characterized by a response in the test group that is considered statistically significant when compared with control signal intensity, wherein the significance level p is preferably equal or less than 0.1, more preferably equal or less than 0.05, and most preferably equal or less than 0.01.

In one aspect of the inventive subject matter, immunodominant antigens are identified from a proteome screen against sera of a population that has been previously exposed to the pathogen. Most preferably, the population is subdivided in several sub-populations to reflect various disease parameters (e.g., active disease, bacillary burden of disease, latent infection, presence of co-infection with HIV, absence of infection, etc.), which can then be correlated with antibody responses to the so identified antigens. It is still further preferred that the screening also provides data on relative reactivities with respect to the antigens and sera of the populations/sub-populations.

It is generally preferred that at least part of the pathogen's genome is obtained and all potential open reading frames and portions thereof are determined in silico. Once the potential genes are identified, suitable primers are determined to provide amplicons of the entire Open Reading Frames (ORFs), or, less preferably, portions thereof, wherein the primers are preferably designed to allow facile subcloning into an expression system. Most preferably, the subcloning uses recombinase-based subcloning using unpurified PCR mixtures to avoid cloning bias, and the so obtained recombinant plasmids are polyclonally multiplied, which enables unbiased presentation of the amplicons. It is still further particularly preferred that the plasmid preparations are then subjected to an in vitro transcription/translation reaction to thereby provide the recombinant ORF peptide, which is then spotted or otherwise immobilized onto a suitable addressable carrier (e.g., membrane, bead, etc.).

It should be recognized that the so prepared proteomes can then be exposed to serum of a population of control individuals and/or population of individuals that are known to have current or previous exposure to the above pathogen from which the ORFs were prepared. Antibodies of the serum that bind to one or more of the ORFs are then detected using well known methods (e.g., use of secondary antibodies). In this manner, the entire proteome of the pathogen can be rapidly assessed for immunogenicity and potential binding with antibodies in serum. Various preferred aspects, compositions, and methods of proteome preparation are disclosed in International patent publication number WO 06/088492, which is incorporated by reference herein.

Therefore, and among various other advantages, it should be especially recognized that contemplated compositions and methods presented herein will allow for preparation of vaccines and diagnostic compositions comprising a plurality of antigens with known and predetermined affinity to target ORFs of a pathogen. As individual immune systems are known to exhibit significant variation with respect to antigen recognition, methods and compositions contemplated herein will allow statistically supported antigen identification to identify immunodominant antigens in a population of patient. Consequently, multiple targets can be used to elicit an immune response and/or detect a prior exposure, even where one or more of the targets may be evasive for detection or provide only a weak response.

With respect to the immunodominant sequences identified herein, it should be further appreciated that the sequences need not be complete ORFs, but that suitable sequences may also be partial sequences (e.g., synthetic, recombinant or isolated) that typically comprise at least part of an antigenic epitope. For example, contemplated DNA sequences include those that will hybridize under stringent hybridization conditions to respective sequences listed in the sequence listing. Thus, sequences contemplated herein may be identified as DNA sequences encoding the antigenic peptide (partial or entire ORF), or may be identified as peptide sequence (or homologs thereof). Similarly, chemically modified antigens, and/or orthologs of the polypeptides presented herein are also deemed suitable for use herein.

It should be particularly noted that while proteome screening will provide a plurality of antigens as potentially useful molecules for diagnosis, vaccination, and/or therapy, such an approach only provides a raw cut of (a plurality) of individual responses. Therefore, as most individual immune reactions towards the same pathogen elicit a significantly distinct profile of antibodies (e.g., depending on disease stage, previous exposure, and/or inter-individual variability), results obtained from such screening are typically inhomogeneous. Consequently, variability of the individual immune responses and variability of the quantity of recombinant protein in the array must be taken into consideration to obtain meaningful results.

Therefore, it should be appreciated that filtering of raw data will result in a collection of antigens with quantified and known relative reactivities with respect to sera of a population infected with the pathogen. Moreover, it should be noted that as signals may be specific to a particular stage in the course of an infection, relative reactivities may be indicative of the time course of the infection, and/or relative reactivities may represent differences in the strength of immunogenicity of the particular antigen (or quantity of deposited antigen in the screening assay). Additionally, it should be particularly recognized that depending on the choice of the specific patient population, the tested sera will reflect the immune status of a population that is characterized by one or more parameters of the disease. For example, populations may be observed that are infected or not infected, that had a long-term exposure or chronic infection, that had spontaneous recovery, that represents a group of responders (or non-responders) to a particular drug treatment, or that had at least partial immunity to the pathogen.

In still further contemplated aspects, immunodominant antigens are identified by selecting for an antigen (preferably within a well-defined sub-population) that (a) produces in at least 40-50% of a population a measurable signal, and (b) has a signal strength of at least 40% of the overall average signal intensity. However, and more preferably, the signal strength will be at least above average of the overall average signal intensity, and even more preferably in the upper tertile (quartile, or even quintile) of signal intensities in the assay. Therefore, and viewed from another perspective, immunodominant antigens will preferably be selected in a comparison of at least two series of tests, wherein one series of tests is typically the sub-population (e.g., primary infection, active disease, latent infection, recovering, previously diseased, chronic, etc.) and the other series of tests is the control group (e.g., other sub-population or control group). Still further, it is generally preferred that the series of tests also include a negative control against which the potential immunodominant antigens are compared.

Consequently, and with particular respect to the pathogen presented herein, it should be appreciated that compositions comprising one or more selected immunodominant antigens can be prepared that will have a statistically high probability to elicit or have elicited an immune response in a relatively large group of patients. Further, where the antigens are determined from selected sub-populations (e.g., active disease, severity of disease, latent infection, previously diseased patients, primary infection, etc.), the antigens also have a known association with a disease parameter and thus allow staging of the disease and/or prediction of therapeutic efficacy. Moreover, as the antigens presented herein are immunodominant antigens, it should be noted that vaccine compositions can be prepared with known or predictable immunogenicity.

More specifically, antigens from M. tuberculosis encoded by the nucleic acids of SEQ ID NO:1 to SEQ ID NO:586 were identified as immunodominant (see examples below). With respect to the reading frame for each of the sequences of SEQ ID NO:1 to SEQ ID NO:586, it should be noted that the first base in the sequences is either the first base of the start codon or the first base in the first codon of the polypeptide that was identified with the methods and compositions provided herein. Most typically, the last three bases denote the stop codon, or the last base of the last codon of the polypeptide that was identified with the methods and compositions provided herein.

In these examples, each of the antigens was characterized, inter alia, with regard to their individual and relative reactivities for the pathogen. Most typically, reactivity was measured as strength of immunogenicity (e.g., such that average binding affinity and/or average quantity of the antibodies produced a predetermined signal intensity (e.g., in the upper half, upper tertile, or even upper quartile)). Viewed from a different perspective, each one of the identified antigens has a known signal strength (reflecting the quantity of antibodies formed in the patient) in the assay as described below relative to another one of the identified antigens. Some proteins, such as the one depicted in FIG. 5, exhibit a tail distribution of higher intensity signals in TB samples that is not seen in non-TB samples. These two violin plots show the distribution of log10-transformed signal intensities measured for a representative protein in sera from TB cases vs. sera from non-TB disease cases. Proteins having this characteristic distribution were identified on the examples described below by implementing a calculation whereby the null hypothesis could be rejected that the profile of a sample comprised only reactivity values consistent with the non-TB intensity distribution.

Furthermore, each of the identified antigens was also characterized by association with at least one parameter. In most cases, the disease parameter was active disease after infection, and in further cases, the disease parameter was number of tubercle bacilli in sputum or radiographic extent of disease, and in further cases, history of past disease in the non-diseased population. Therefore, it should be especially appreciated that identification of immunodominant antigens will not only allow for identification of statistically meaningful antigens for diagnosis, vaccine development, and treatment, but also allow to develop a stage specific tool to identify candidate molecules to fine-tune diagnosis and/or treatment.

For example, suitable diagnostic devices especially include those comprising one or more of the immunodominant antigens, fragments, or analogs thereof that are encoded by nucleic acids according to SEQ ID NO:1 to SEQ ID NO:586, preferably Rv0798c (SEQ ID NO:121), Rv1886c (SEQ ID NO:270), Rv2031c (SEQ ID NO:284), Rv3616c (SEQ ID NO:509), Rv3804c (SEQ ID NO:534), Rv3874 (SEQ ID NO:547), Rv0302 (SEQ ID NO:52), Rv0379 (SEQ ID NO:65), Rv0394c (SEQ ID NO:66), Rv0456c (SEQ ID NO:74), Rv0632c (SEQ ID NO:103), Rv0944 (SEQ ID NO:142), Rv0984(SEQ ID NO:146), Rv1030 (SEQ ID NO:153), Rv1196 (SEQ ID NO:174), Rv1242 (SEQ ID NO:180), Rv1284 (SEQ ID NO:187), Rv1387 (SEQ ID NO:206), Rv1837c (SEQ ID NO:264), Rv1926c (SEQ ID NO:275), Rv1980c (SEQ ID NO:281), Rv2094c (SEQ ID NO:294), Rv2544 (SEQ ID NO:363), Rv2618 (SEQ ID NO:375), Rv2746c (SEQ ID NO:391), Rv2870c (SEQ ID NO:407), Rv2873 (SEQ ID NO:408), Rv2875 (SEQ ID NO:409), Rv3050c (SEQ ID NO:434), Rv3248c (SEQ ID NO:458), Rv3376 (SEQ ID NO:478), Rv3763 (SEQ ID NO:527), Rv3810 (SEQ ID NO:536), Rv3864 (SEQ ID NO:545), Rv2252 (SEQ ID NO:323), Rv2282c (SEQ ID NO:569), Rv0212c (SEQ ID NO:557), Rv3243c (SEQ ID NO:456), Rv3675 (SEQ ID NO:519), Rv2984 (SEQ ID NO:423), Rv1175c (SEQ ID NO:169), Rv3326 (SEQ ID NO:578), Rv3628 (SEQ ID NO:513), Rv3775 (SEQ ID NO:584), Rv3362c (SEQ ID NO:475), Rv0801 (SEQ ID NO:122), Rv1629 (SEQ ID NO:566), Rv0272c (SEQ ID NO:558), Rv3762c (SEQ ID NO:583), Rv3319 (SEQ ID NO:577), Rv3495c (SEQ ID NO:581), Rv2151c (SEQ ID NO:308), Rv0227c(SEQ ID NO:37), Rv0280(SEQ ID NO:50), Rv0993 (SEQ ID NO:148), Rv1306 (SEQ ID NO:192), Rv1363c (SEQ ID NO:204), Rv2050 (SEQ ID NO:288), Rv2116 (SEQ ID NO:299), Rv3417c (SEQ ID NO:486), Rv3653 (SEQ ID NO:516), Rv1253 (SEQ ID NO:182), Rv3413c (SEQ ID NO:485), Rv1635c (SEQ ID NO:232), Rv3021c (SEQ ID NO:432), Rv1193 (SEQ ID NO:173), Rv2592c (SEQ ID NO:369), Rv3620c (SEQ ID NO:510), Rv0929 (SEQ ID NO:139), Rv0959 (SEQ ID NO:145), Rv1162 (SEQ ID NO:166), Rv2389c (SEQ ID NO:341), Rv2984 (SEQ ID NO:423), Rv2588c (SEQ ID NO:367), Rv0171 (SEQ ID NO:26), Rv1865c (SEQ ID NO:267), Rv2074 (SEQ ID NO:290), Rv0543c (SEQ ID NO:87), Rv1677 (SEQ ID NO:237), Rv1304 (SEQ ID NO:191), Rv2841c (SEQ ID NO:400), Rv3680 (SEQ ID NO:520), Rv0831c (SEQ ID NO:125), Rv2032 (SEQ ID NO:285), Rv3127 (SEQ ID NO:446), Rv3272 (SEQ ID NO:464), Rv3323c (SEQ ID NO:470), Rv3508 (SEQ ID NO:494), Rv3628 (SEQ ID NO:513), Rv1173 (SEQ ID NO:167), Rv2623 (SEQ ID NO:376), Rv0527 (SEQ ID NO:85), Rv1620c (SEQ ID NO:229), Rv1901 (SEQ ID NO:272), Rv2151c (SEQ ID NO:308), Rv0362 (SEQ ID NO:60), Rv3129 (SEQ ID NO:447), Rv3140 (SEQ ID NO:449), Rv0340 (SEQ ID NO:56), Rv2792c (SEQ ID NO:395), Rv3003c (SEQ ID NO:426), Rv3019c (SEQ ID NO:431), Rv3862c (SEQ ID NO:544), Rv0572c (SEQ ID NO:91), Rv2477c (SEQ ID NO:356), Rv2659c (SEQ ID NO:379), Rv0311 (SEQ ID NO:54), Rv0350 (SEQ ID NO:57), Rv2127 (SEQ ID NO:301), Rv3875 (SEQ ID NO:548), Rv0877 (SEQ ID NO:134), Rv1916 (SEQ ID NO:274), Rv2138 (SEQ ID NO:303), Rv2847c (SEQ ID NO:403), Rv3118 (SEQ ID NO:444), Rv2495c (SEQ ID NO:358), Rv3669 (SEQ ID NO:517), Rv0281 (SEQ ID NO:51), Rv2711 (SEQ ID NO:383), Rv2744c (SEQ ID NO:390), Rv3803c (SEQ ID NO:533), Rv1239c (SEQ ID NO:179), Rv2147c (SEQ ID NO:307), Rv2253 (SEQ ID NO:324), Rv0308 (SEQ ID NO:53), Rv0587 (SEQ ID NO:95), Rv1564c (SEQ ID NO:224), Rv2185c (SEQ ID NO:313), Rv1805c (SEQ ID NO:261), Rv2729c (SEQ ID NO:386), Rv3386 (SEQ ID NO:481), Rv3515c (SEQ ID NO:497), Rv0772 (SEQ ID NO:116), Rv2948c (SEQ ID NO:420), Rv0006 (SEQ ID NO:1), Rv1906c (SEQ ID NO:273), Rv2244 (SEQ ID NO:322), Rv2468c (SEQ ID NO:354), Rv3701c (SEQ ID NO:522), Rv0054 (SEQ ID NO:6), Rv1945 (SEQ ID NO:277), Rv3345c (SEQ ID NO:472), Rv0276 (SEQ ID NO:48), Rv0709 (SEQ ID NO:108), Rv1527c (SEQ ID NO:220), Rv2048c (SEQ ID NO:287), Rv2414c (SEQ ID NO:345), Rv3524 (SEQ ID NO:499), Rv3556c (SEQ ID NO:502), Rv1322 (SEQ ID NO:196), Rv2934 (SEQ ID NO:417), Rv0270 (SEQ ID NO:47), Rv0612 (SEQ ID NO:99), Rv1699 (SEQ ID NO:242), Rv2728c (SEQ ID NO:385), Rv3017c (SEQ ID NO:430), Rv3364c (SEQ ID NO:476), Rv3418c (SEQ ID NO:487), Rv3718c (SEQ ID NO:525), Rv0426c (SEQ ID NO:70), Rv1181 (SEQ ID NO:171), Rv1725c (SEQ ID NO:250), Rv0256c (SEQ ID NO:44), Rv0605 (SEQ ID NO:98), Rv0737 (SEQ ID NO:114), Rv0834c (SEQ ID NO:126), Rv1255c (SEQ ID NO:184), Rv2224c (SEQ ID NO:320), Rv1843c (SEQ ID NO:265), Rv2333c (SEQ ID NO:334), Rv2490c (SEQ ID NO:357), Rv3183 (SEQ ID NO:454), Rv0668 (SEQ ID NO:106), Rv1556 (SEQ ID NO:223), Rv1673c (SEQ ID NO:236), Rv3513c (SEQ ID NO:496), Rv3675 (SEQ ID NO:519), Rv3870 (SEQ ID NO:546), Rv3891c (SEQ ID NO:552), Rv0163 (SEQ ID NO:24), Rv0710 (SEQ ID NO:109), Rv1297 (SEQ ID NO:189), Rv1745c (SEQ ID NO:255), Rv0600c (SEQ ID NO:97), Rv1536 (SEQ ID NO:222), Rv1738 (SEQ ID NO:254), Rv2524c (SEQ ID NO:359), Rv3086 (SEQ ID NO:440), Rv3367 (SEQ ID NO:477), Rv0135c (SEQ ID NO:20), Rv0627 (SEQ ID NO:101), Rv1448c (SEQ ID NO:213), Rv3224a (SEQ ID NO:455), Rv0029 (SEQ ID NO:2), Rv0846c (SEQ ID NO:129), Rv1159 (SEQ ID NO:165), Rv1186c (SEQ ID NO:172), Rv1705c (SEQ ID NO:243), Rv1713 (SEQ ID NO:248), Rv2476c (SEQ ID NO:355), Rv3402c (SEQ ID NO:483), Rv2615c (SEQ ID NO:374), Rv2995c (SEQ ID NO:425), Rv3788 (SEQ ID NO:585), Rv0140 (SEQ ID NO:555), Rv0203 (SEQ ID NO:33), Rv1531 (SEQ ID NO:565), Rv1693 (SEQ ID NO:241), Rv1882c (SEQ ID NO:269), Rv2143 (SEQ ID NO:568), Rv2367c (SEQ ID NO:570), Rv0584 (SEQ ID NO:94), Rv1651c (SEQ ID NO:567), Rv3197a (SEQ ID NO:576), Rv3369 (SEQ ID NO:579), Rv3825c (SEQ ID NO:586), Rv0101 (SEQ ID NO:15), Rv0808 (SEQ ID NO:123), Rv0814c (SEQ ID NO:560), Rv2153c (SEQ ID NO:309), Rv2933 (SEQ ID NO:416), Rv0071 (SEQ ID NO:9), Rv2471 (SEQ ID NO:571), Rv2979c (SEQ ID NO:575), Rv0155 (SEQ ID NO:556), Rv0581 (SEQ ID NO:559), Rv2631 (SEQ ID NO:377), Rv3455c (SEQ ID NO:489), Rv3601c (SEQ ID NO:505), Rv0896 (SEQ ID NO:562), Rv1641 (SEQ ID NO:234), Rv3005c (SEQ ID NO:427), Rv3759c (SEQ ID NO:582), Rv3800c (SEQ ID NO:532), Rv0187 (SEQ ID NO:30), Rv2379c (SEQ ID NO:338), Rv2434c (SEQ ID NO:352), Rv2940c (SEQ ID NO:574), Rv3477 (SEQ ID NO:580), Rv0435c (SEQ ID NO:72), Rv0844c (SEQ ID NO:128), Rv0856 (SEQ ID NO:561), Rv1191 (SEQ ID NO:564), Rv2803 (SEQ ID NO:397), Rv0783c (SEQ ID NO:118), Rv1054 (SEQ ID NO:563), Rv1689 (SEQ ID NO:240), Rv2539c (SEQ ID NO:572), Rv2859c (SEQ ID NO:573), Rv3777 (SEQ ID NO:528).

Depending on the particular device format, the device may have only a single immunodominant antigen, fragment, or analog that may be used for detection of binding of antibodies from blood, plasma or serum or other bodily fluids containing antibody in an automated manner or by visual observation. For example, where a single immunodominant antigen is employed, suitable devices may be in the format of a dipstick or competitive ELISA. On the other hand, where multiple immunodominant antigens are employed, suitable devices may be in the format of an array that can be read in an automated device (e.g., via scanner) or visual manner (e.g., dye-forming colorimetric reaction). Most typically, in such devices, the plurality of antigens is deposited in a spatially addressable manner (e.g., x-y matrix or beads with color association or microtiter plate). Moreover, it should be noted that diagnostic devices contemplated herein may be based on numerous well known manners of detection, including ELISA (sandwich or non-sandwich), competitive ELISA, anti-idiotypic antibodies, etc., wherein all known colorimetric and photometric (e.g., fluorescence, luminescence, etc.) or radiometric reactions are deemed suitable for use.

In most typical devices, a plurality of immunodominant antigens of a single (or multiple) pathogen and/or serotype are deposited on a solid surface or onto an addressable solid phase and exposed to blood, serum, plasma or other antibody-containing body fluid. Consequently, so prepared compositions can be employed to identify and/or characterize an immune response of an individual against selected antigens, and optionally assess the kind of immune response (e.g., identification of latent or chronic infection), as well as disease progression, efficacy of therapy, etc. Most typically, the plurality of antigens will include between 5 to 10 antigens, but significantly higher amounts of antigens are also contemplated, including at least 25%, more typically at least 50%, even more typically at least 75%, and most typically at least 90% of the proteome of the pathogen. Similarly, less than 5 antigens (1-4) are also deemed suitable. In further typical aspects of the inventive subject matter, contemplated arrays are most preferably processed in a microfluidic device. For example, an array of antigens in such devices may be printed on a membrane or other material (e.g., nitrocellulose-coated carrier of less than 1 cm2 area) that is then placed in a microfluidic device having sample/reagent inlet and outlet ports. Depending on the specific configuration, signals may be acquired using optical methods (e.g., CCD chip, flat bed scanner, etc.), electrical methods (e.g., voltametric or amperometric), or other methods well known in the art. Alternatively, visual detection or detection using a regular flat bed scanner at 1200 dpi resolution and/or fluorescence detection is also deemed suitable.

In another example, immunodominant antigens according to the inventive subject matter may also be employed to generate an antibody preparation that can be used as passive vaccination for therapeutic treatment of tuberculosis. In preferred embodiments, such vaccines are subunit vaccines or attenuated live recombinant vaccines. For example, the immunodominant antigens presented herein may be employed in the manufacture of a vaccine that comprises at least one, and more typically at least two of the immunodominant antigens encoded by nucleic acids according to SEQ ID NO:1 to SEQ ID NO:586. More preferably, however, contemplated vaccines will include between two and five, or at least six, and even more antigens, of which at least one of the antigens is an immunodominant antigen. Such vaccine compositions may be directed to elicit immunity against single or multiple subtypes and may thus comprise distinct immunodominant antigens, optionally from multiple and distinct subtypes. Moreover, it should be appreciated that vaccines may be produced that predominantly, or even exclusively, comprise immunodominant antigens of a single parameter. For example, a vaccine may comprise immunodominant antigens that are characteristic for a population that has a latent infection. In less preferred aspects, the sequences according to SEQ ID NO:1 to SEQ ID NO:586 may also be employed as DNA vaccines, or be part of an in vivo expression system that triggers an immune response against the in vivo produced recombinant antigen or fragment thereof.

Additionally, it is contemplated that antigens identified herein may also be employed to generate (monoclonal or polyclonal) antibodies or fragments thereof (e.g., Fab, scFv, etc.) that can then be employed in a diagnostic test that directly detects the presence of the antigen in blood, blood derivatives or other body fluid of a patient where the antigen is circulating in the patient. Of course, it should be appreciated that the antigen may circulate in association with the pathogen, in association with components of the pathogen, in free form, or bound to a molecule or cell of the patient. Most preferably, the antigens are immunodominant and/or serodiagnostic antigens as presented herein. For example, suitable tests include those in which one or more labeled antibodies are used to detect presence of the antigen in bodily fluid where the antigen may be captured (specifically or in bulk with other proteins) on a surface. There are numerous antigen detection methods known in the art and all of the known formats are deemed suitable for use herein.

In certain embodiments, the diagnostic tools of the present invention involve the recognition of the immunodominant antigens described herein in an in vitro cellular assay determining the release of cytokines, such as interferon gamma, from lymphocytes withdrawn from a subject currently or previously infected with a virulent mycobacterium.

With respect to suitable formulations of vaccines, it should be recognized that all known manners of producing such vaccines are deemed appropriate for use herein, and a person of ordinary skill in the art will be readily able to produce such vaccines without undue experimentation (see e.g., “Vaccine Adjuvants and Delivery Systems” by Manmohan Singh; Wiley-Interscience (Jun. 29, 2007), ISBN: 0471739073; or “Vaccine Protocols” (Methods in Molecular Medicine) by Andrew Robinson, Martin P. Cranage, and Michael J. Hudson; Humana Press; 2 edition (Aug. 27, 2003); ISBN: 1588291405). Therefore, suitable vaccines may be formulated as injectable solutions, or suspensions, intranasal formulations, transdermal or oral formulations.

The compositions, vaccines, diagnostic tests, etc., described herein may be used for both human and veterinary use.

EXAMPLES

M. tuberculosis proteome microarray chip fabrication and probing methods: Proteome microarrays were fabricated as described previously (Proc Natl Acad Sci USA 102(3): 547-552; Proteomics 7(10): 1678-1686; Proteomics 7(13): 2172-2183) with modifications. This and all other extrinsic materials discussed herein are incorporated by reference in their entirety. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.

High-throughput construction of the M. tuberculosis ORFeome: Using the available M. tuberculosis sequence data primer pairs were designed for all ORFs encoded in the genome. Quality control was performed using gel electrophoresis of PCR products. After three rounds of PCR, the final tally was 97.3% successfully amplified. For cloning, PCR products were mixed with a linearized pXT7-based expression vector as described previously and transformed into supercompetent DH5α cells. The transformed cells were cultured at 37° C. with vigorous aeration and were checked for turbidity the following day. DNA was purified from the overnight cultures without prior colony selection using QIAprep 96 Turbo Miniprep Kits from Qiagen. Of the 3998 successfully amplified PCR products, 3858 were cloned into the pXi vector (96.5% efficiency). A random sample of 1064 clones were tested by ‘QC-PCR’ in which using the sequence-specific primers were again used to verify that the cloned inserts were the expected size. Of these, 1007 were verified (94.6%) using this methodology.

More specifically, 4109 primer pairs were designed to amplify every ORF in the M. tuberculosis (strain H37Rv) genome annotated in Tuberculist (http://genolist.pasteur.fr/TubercuList/). Custom PCR primers comprising 20 bp of gene-specific sequence with 33 bp of “adapter” sequences were used in PCRs with genomic DNA as template. For genes >3 kb, additional primer pairs were designed to amplify overlapping fragments of 3 kb each. All primer pairs used for this work are published at the UCI Institute for Genomics and Bioinformatics (IGB) web portal at http://contact14.ics.uci.edu/virus/tuber_index.php. The adapter sequences, which become incorporated into the termini flanking the amplified gene, are homologous to the cloning site of the linearized T7 expression vector pXT7 and allow the PCR products to be cloned by in vivo homologous recombination in competent DH5a cells. The resulting protein incorporates an ATG translation start codon, a 5′ polyhistidine epitope, a 3′ influenza hemagglutinin epitope and a T7 terminator.

Array fabrication: Antibodies against the N-terminal poly-His and the C-terminal HA tags engineered into each protein were used to monitor the expression in each spot. Positive and negative controls were built into every array and remaining spots on the array were in vitro transcription/translation reactions expressing 4109 different M. tuberculosis clones representing the entire cloned ORFeome. Once RTS reactions were printed onto nitrocellulose and dried, no appreciable degradation was observed after 6 months of storage in a desiccator at 18° C. (data not shown). However, a reduction in signal and a reduced signal-to-noise ratio associated with prolonged delay in printing after the end of the 5 h in vitro protein expression was observed. To minimize such reduction, in vitro expression reactions were staggered through the print run. Thus, it is generally preferred that the reactions are no more than 5, more preferably no more than 3, and most preferably no more than 1 hour old before printing. Remaining variance in signals was normalized using positive and negative controls as described below.

Microarray chips were fabricated in batches of 50-100 2-pad slides (i.e., 100-200 arrays). Two standard deviations above the average of the negative control intensity was used as a cut-off for detection of the tags. Overall, 3854 (96.4%) of the expressed proteins were positive for the HIS tag, 3730 (93.3%) were positive for the HA tag, 3538 (91%) were positive for both tags, and only 56 (1.4%) were negative for both tags, which means 98.6% of the expressed proteins were positive for at least 1 of the tags.

In more detail, purified minipreps of DNA of 4109 clones (3998 full length ORFs plus 111 segments of ORFs >3kb) were expressed in the E. coli based in vitro transcription/translation expression system from Roche (RTS-100). 10 μl in vitro reactions were set up in sealed 384 well plates and incubated for 5 h at 30° C. in a platform microshaker at 300 RPM. A mixture of Tween-20 to a final concentration of 0.05% and a protease inhibitor cocktail (Complete, Roche) were then added. To minimize delay in printing after completion of protein expression, the initiation of the RTS reactions was staggered. The RTS reactions were printed in singlicate without further purification onto 2-pad nitrocellulose-coated FAST slides (Whatman) using an Omni Grid 100 microarray printer (Genomic Solutions) in 4×4 sub-array format, with each subarray comprising 17×17 spots. Each sub-array included 6 negative control spots comprising ‘mock’ RTS reactions lacking DNA template. Each sub-array also included positive control spots of 5 serial dilutions of mouse, rat and human whole IgG. Together these positive and negative controls are used to normalize the data from different arrays (infra). Also included were 4 serial dilutions of purified recombinant Epstein-Barr virus nuclear antigen-1 (EBNA-1) which is recognized by the majority of humans and which serves as a useful guide to serum quality. Also printed were three recombinant M. tuberculosis proteins, 38 KDa (Rv0934), CFP-10 (Rv3874 (SEQ ID NO:547)), and ESAT-6 (Rv3875 (SEQ ID NO:548)). In addition, 6 serial dilutions of recombinant vascular endothelial growth factor (VEGF) from Invitrogen (Carlsbad Calif.) and tumor necrosis factor-α (TNF-α) were printed to be used as a hybridization controls by ‘spiking-in’ monoclonal anti-VEGF and anti-TNF-α antibodies into certain sera samples.

For probing with sera, the sera were diluted to 1/200 in Low Cross Dilution Buffer (Candor Bioscience) containing E. coli lysate at a final concentration of 4-5 mg/ml protein, and incubated at room temperature for 30 minutes with constant mixing to block anti-E. coli antibodies. The arrays were rehydrated in blocking buffer (Candor Bioscience) for 30 min and probed with the pretreated sera overnight at 4° C. with constant agitation. The slides were then washed 5× in tris(hydroxymethyl)aminomethane (Tris)-buffered saline containing 0.05% (v/v) Tween 20, (T-TBS) and incubated in biotinylated anti-human IgG-Fc (Jackson Immuno Research) diluted 1/400 in dilution buffer. After washing the slides three times each in T-TBS, bound antibodies were visualized by incubation with streptavidin-conjugated SureLight® P-3 (Columbia Biosciences). The slides were then washed three times each in T-TBS followed by TBS, and dipped in distilled water prior to air drying by brief centrifugation. Protein expression was monitored on the printed array by probing with monoclonal anti-polyhistidine (clone His-1, Sigma) and anti-hemagglutinin (clone 3F10, Roche) using biotinylated anti-mouse and anti-rat secondary antibodies, respectively followed by streptavidin-conjugated SureLight® P-3.

Human sera: Sera were obtained from 927 patients enrolled from clinical sites in several TB-endemic areas of the world using a cohort design that included individuals presenting with respiratory symptoms suggestive of TB (TB suspects). Diagnosis of active TB was made on the basis of evidence of growth of M. tuberculosis from sputum of patients (culture-confirmed active TB) (n=403). Diagnosis of non-TB disease was made on the basis of full microbiological and chest X ray (CXR) investigations (n=418). Non-TB disease cases included were those not treated empirically for TB and who received adequate follow-up by symptom screen, and CXR at times, to exclude TB. BCG vaccination status was not always known, but cohorts were all from countries that implement universal BCG vaccination at birth. For data analysis, active TB cases were subdivided in smear positive TB (presence of M. tuberculosis in sputum) and smear negative active TB. Cases in the TB and non-TB disease group were also subdivided based on HIV comorbidity. Negative control sera (n=42) were obtained from healthy, asymptomatic individuals from a non-endemic country (Italy) who were confirmed latent TB infection (LTBI)-negative by tuberculin skin test, Quantiferon assay and tuberculosis ELISPOT (T-spot) assay. The BCG vaccination status of this latter set of donors is not known, but generally, individuals from endemic countries are vaccinated and those from non-endemic countries are not.

Data acquisition: Slides were scanned using a GenePix Autoloader 4200AL microarray confocal laser scanner (Molecular Devices) Median pixel intensity of the spots were quantified from tiff image files of probed array scans using GenePix Pro 6.0 software (Molecular Devices).

Classification of immunoreactive antigens by proteomic features and function: Antigens were classified according to the Functional Classification Codes annotated on TubercuList, Computational predictions were also made using SignalP (J Mol Biol 340(4): 783-795) and PSORTb (Bioinformatics 21(5): 617-623) (http://db.psort.org) to predict the presence probability of signal peptides and cellular localization, respectively.

Screening the proteome for serodiagnostic antigens: Representative arrays probed with serum from each group are shown in FIGS. 1A and 1B. Here, panel (A) shows culture-confirmed TB-positive individual, and panel (B) shows latent TB infected-negative control individual. Each array contained positive and negative control spots. The IgG control spots, which control for secondary antibody, were positive in both arrays. Neither individuals reacted with the negative (‘no DNA’) control reactions. Both groups of individuals reacted to EBNA-1, indicating prior exposure to EBV, and the group of acute infected individuals, had a robust antibody response to several M. tuberculosis antigens.

One evaluation of the array was performed by calculating a cut-off value above the mean +2 SD of the control (‘no DNA’) signals. By this criterion it was noted that sera from both TB-positive and control individuals reacted to antigens on the array. Even by visual estimation, however, it was evident that TB-confirmed patients reacted more intensely and against more antigens than the controls. To determine whether the signals seen for M. tuberculosis antigens were E. coli-specific antibodies against which blocking had failed, E. coli lysate concentration was increased. However, this had no effect on these signals (data not shown). Lysate prepared from M. tuberculosis was also included with the result that this completely abolished all signals on the array (data not shown), which indicates that the signals seen on the array are due to M. tuberculosis-specific antibodies in the sera.

Protein Microarray Data Analysis:

Microarray data were analyzed by four methods, summarized below. Log10-transformed data were used for first three methods and VSN-normalized data were used for the fourth method. FIG. 4A shows proteins ranking <10 in at least one of three analytical methods (random forests, CERNO, and random forests with CERNO-prefiltered data) in a comparison between TB cases (n=400) and non-TB disease cases (n=418). Relative ranks of proteins (max rank ˜4000) in each method are shown. N/A, not available; this implies that the protein was pre-filtered by CERNO (p value for filtration >0.005). FIG. 4B shows the same as FIG. 4A, but for a comparison between TB cases (n=255) and non-TB disease cases (n=307) among HIV negative persons only.

1. TB and non-TB samples were classified by Random Forests, a classification method based on multiple classification trees. Random forests queries (comparisons of TB to non-TB disease classes) were performed with data collected from sera from endemic countries, and with data stratified for HIV status and for smear status of TB patients. Antigens were ranked from most informative to least informative based on mean decrease accuracy output of a particular query (highest mean decrease accuracy corresponds to highest rank). The random forests analysis was conducted with and without a pre-filtering step using the CERNO statistical calculation.

2. CERNO p-values provide an association of high relative intensities with active tuberculosis diagnosis. Antigens were ranked by decreasing p-value.

3. The data were also analyzed to identify antigens that exhibit unusually high binding in TB samples relative to the non-TB disease samples by the following, sequential calculations: (i) the mean and variance for each antigen in non-TB from endemic areas; (ii) a Z score (number of standard deviations from the mean for an antigen in the non-TB disease class) for each antigen in each sample in one comparison (TB vs non-TB disease from endemic countries); (iii) a p-value corresponding to the Z score (expected normal distribution tail area above the value); (iv) the adjusted p-values (Benjamini-Hochberg) for each profile; (v) reactivity vs no reactivity at the p-adjusted level of 0.01 (false discovery rate of one percent). Antigens were ranked by number of reactivity calls in the TB group.

4. To stabilize variance of the raw data, a variant of the log-transformation (asinh) was used (Bioinformatics 20(5): 660-667), and negative and positive control spots (the ‘no DNA’ and IgG spots, respectively) were used to normalize the data using the “VSN” package in R from the Bioconductor suite (http://Bioconductor.org/). A p-value on the normalized data was prepared by comparing signals between the confirmed TB-positive and LTBI-negative control groups using a Bayes-regularized t-test adapted from Cyber-T for use with protein arrays (Bioinformatics 17(6): 509-519; J Biol Chem 276(23): 19937-19944; Bioinformatics 22(14): 1760-1766; Bioinformatics 23(13): i508-518). To account for multiple test conditions, Benjamin Hochberg p-value adjustments were calculated. Reactive antigens were defined as serodiagnostic or cross-reactive by having a Benjamini Hochberg corrected p-value <0.05 or >0.05, respectively, and an average signal intensity >2 std. dev above the mean of the negative control (no DNA) spots on the smear positive samples. Multiple antigen classifiers were built using Support Vector Machines (SVMs). The “e1071” and “ROCK” packages in R were utilized to train the SVMs and to produce receiver operating characteristic (ROC) curves, respectively. For other graphic representations such as heat maps and histograms, normalized data were retransformed into approximate raw values.

With the methods above, a total of 250 antigens were selected by combining top 50 ranks from Random Forests (RF) and CERNO for queries on all TB and non-TB disease patients, all HIV negative TB and non-TB disease patients (with and without stratification by smear), plus top 10 ranks for HIV-positive TB and non-TB disease query, plus reactivity calls of >3 in TB category, plus Benjamini Hochberg adjusted Cyber T p value <0.05. Seven sets of antigens were prioritized based on agreement by the methods, with the antigens of the first set being the most preferred.

The most preferred sequences encoding the antigens were characterized by RF or CERNO (p<0.005) plus reactivity calls, RF (<10) and CERNO (p <0.005), and Benjamini Hochberg adjusted Cyber T p value <0.05: Rv0798c (SEQ ID NO: 121), Rv1886c (SEQ ID NO:270), Rv2031c (SEQ ID NO:284), Rv3616c (SEQ ID NO:509), Rv3804c (SEQ ID NO:534), Rv3874 (SEQ ID NO:547).

The following sequences producing the antigens were determined to be second most preferential, characterized by RF or CERNO (p<0.005) plus reactivity calls, RF (<10) and CERNO (p<0.005): Rv0302 (SEQ ID NO:52), Rv0379 (SEQ ID NO:65), Rv0394c (SEQ ID NO:66), Rv0456c (SEQ ID NO:74), Rv0632c (SEQ ID NO:103), Rv0944 (SEQ ID NO:142), Rv0984 (SEQ ID NO:146), Rv1030 (SEQ ID NO:153), Rv1196 (SEQ ID NO:174), Rv1242 (SEQ ID NO:180), Rv1284 (SEQ ID NO:187), Rv1387 (SEQ ID NO:206), Rv1837c (SEQ ID NO:264), Rv1926c (SEQ ID NO:275), Rv1980c (SEQ ID NO:281), Rv2094c (SEQ ID NO:294), Rv2544 (SEQ ID NO:363), Rv2618 (SEQ ID NO:375), Rv2746c (SEQ ID NO:391), Rv2870c (SEQ ID NO:407), Rv2873 (SEQ ID NO:408), Rv2875 (SEQ ID NO:409), Rv3050c (SEQ ID NO:434), Rv3248c (SEQ ID NO:458), Rv3376 (SEQ ID NO:478), Rv3763 (SEQ ID NO:527), Rv3810 (SEQ ID NO:536), Rv3864 (SEQ ID NO:545).

The following sequences producing the antigens were determined to be third most preferential, characterized by Benjamini Hochberg adjusted Cyber T p value <0.05: Rv2252 (SEQ ID NO:323), Rv2282c (SEQ ID NO:569), Rv0212c (SEQ ID NO:557), Rv3243c (SEQ ID NO:456), Rv3675 (SEQ ID NO:519), Rv2984 (SEQ ID NO:423), Rv1175c (SEQ ID NO:169), Rv3326 (SEQ ID NO:578), Rv3628 (SEQ ID NO:513), Rv3775 (SEQ ID NO:584), Rv3362c (SEQ ID NO:475), Rv0801 (SEQ ID NO:122), Rv1629 (SEQ ID NO:566), Rv0272c (SEQ ID NO:558), Rv3762c (SEQ ID NO:583), Rv3319 (SEQ ID NO:577), Rv3495c (SEQ ID NO:581), Rv2151c (SEQ ID NO:308).

The following sequences producing the antigens were determined to be fourth most preferential, characterized by reactivity calls: Rv0227c(SEQ ID NO:37), Rv0280(SEQ ID NO:50), Rv0993 (SEQ ID NO:148), Rv1306 (SEQ ID NO:192), Rv1363c (SEQ ID NO:204), Rv2050 (SEQ ID NO:288), Rv2116 (SEQ ID NO:299), Rv3417c (SEQ ID NO:486), Rv3653 (SEQ ID NO:516).

The following sequences producing the antigens were determined to be fifth most preferential, characterized by ranks <10 by either CERNO or RF: Rv1253 (SEQ ID NO:182), Rv3413c (SEQ ID NO:485), Rv1635c (SEQ ID NO:232), Rv3021c (SEQ ID NO:432), Rv1193 (SEQ ID NO:173), Rv2592c (SEQ ID NO:369), Rv3620c (SEQ ID NO:510), Rv0929 (SEQ ID NO:139), Rv0959 (SEQ ID NO:145), Rv1162 (SEQ ID NO:166), Rv2389c (SEQ ID NO:341), Rv2984 (SEQ ID NO:423), Rv2588c (SEQ ID NO:367), Rv0171 (SEQ ID NO:26), Rv1865c (SEQ ID NO:267), Rv2074 (SEQ ID NO:290).

The following sequences producing the antigens were determined to be sixth most preferential, characterized by ranks <25 by either CERNO or RF: Rv0543c (SEQ ID NO:87), Rv1677 (SEQ ID NO:237), Rv1304 (SEQ ID NO:191), Rv2841c (SEQ ID NO:400), Rv3680 (SEQ ID NO:520), Rv0831c (SEQ ID NO:125), Rv2032 (SEQ ID NO:285), Rv3127 (SEQ ID NO:446), Rv3272 (SEQ ID NO:464), Rv3323c (SEQ ID NO:470), Rv3508 (SEQ ID NO:494), Rv3628 (SEQ ID NO:513), Rv1173 (SEQ ID NO:167), Rv2623 (SEQ ID NO:376), Rv0527 (SEQ ID NO:85), Rv1620c (SEQ ID NO:229), Rv1901 (SEQ ID NO:272), Rv2151c (SEQ ID NO:308), Rv0362 (SEQ ID NO:60), Rv3129 (SEQ ID NO:447), Rv3140 (SEQ ID NO:449), Rv0340 (SEQ ID NO:56), Rv2792c (SEQ ID NO:395), Rv3003c (SEQ ID NO:426), Rv3019c (SEQ ID NO:431), Rv3862c (SEQ ID NO:544), Rv0572c (SEQ ID NO:91), Rv2477c (SEQ ID NO:356), Rv2659c (SEQ ID NO:379), Rv0311 (SEQ ID NO:54), Rv0350 (SEQ ID NO:57), Rv2127 (SEQ ID NO:301), Rv3875 (SEQ ID NO:548), Rv0877 (SEQ ID NO:134), Rv1916 (SEQ ID NO:274), Rv2138 (SEQ ID NO:303), Rv2847c (SEQ ID NO:403), Rv3118 (SEQ ID NO:444), Rv2495c (SEQ ID NO:358), Rv3669 (SEQ ID NO:517), Rv0281 (SEQ ID NO:51), Rv2711 (SEQ ID NO:383), Rv2744c (SEQ ID NO:390), Rv3803c (SEQ ID NO:533), Rv1239c (SEQ ID NO:179), Rv2147c (SEQ ID NO:307), Rv2253 (SEQ ID NO:324), Rv0308 (SEQ ID NO:53), Rv0587 (SEQ ID NO:95), Rv1564c (SEQ ID NO:224), Rv2185c (SEQ ID NO:313).

The following sequences producing the antigens were determined to be seventh most preferential, characterized by ranks between 26 and 50 by either CERNO or RF: Rv1805c (SEQ ID NO:261), Rv2729c (SEQ ID NO:386), Rv3386 (SEQ ID NO:481), Rv3515c (SEQ ID NO:497), Rv0772 (SEQ ID NO:116), Rv2948c (SEQ ID NO:420), Rv0006 (SEQ ID NO:1), Rv1906c (SEQ ID NO:273), Rv2244 (SEQ ID NO:322), Rv2468c (SEQ ID NO:354), Rv3701c (SEQ ID NO:522), Rv0054 (SEQ ID NO:6), Rv1945 (SEQ ID NO:277), Rv3345c (SEQ ID NO:472), Rv0276 (SEQ ID NO:48), Rv0709 (SEQ ID NO:108), Rv1527c (SEQ ID NO:220), Rv2048c (SEQ ID NO:287), Rv2414c (SEQ ID NO:345), Rv3524 (SEQ ID NO:499), Rv3556c (SEQ ID NO:502), Rv1322 (SEQ ID NO:196), Rv2934 (SEQ ID NO:417), Rv0270 (SEQ ID NO:47), Rv0612 (SEQ ID NO:99), Rv1699 (SEQ ID NO:242), Rv2728c (SEQ ID NO:385), Rv3017c (SEQ ID NO:430), Rv3364c (SEQ ID NO:476), Rv3418c (SEQ ID NO:487), Rv3718c (SEQ ID NO:525), Rv0426c (SEQ ID NO:70), Rv1181 (SEQ ID NO:171), Rv1725c (SEQ ID NO:250), Rv0256c (SEQ ID NO:44), Rv0605 (SEQ ID NO:98), Rv0737 (SEQ ID NO:114), Rv0834c (SEQ ID NO:126), Rv1255c (SEQ ID NO:184), Rv2224c (SEQ ID NO:320), Rv1843c (SEQ ID NO:265), Rv2333c (SEQ ID NO:334), Rv2490c (SEQ ID NO:357), Rv3183 (SEQ ID NO:454), Rv0668 (SEQ ID NO:106), Rv1556 (SEQ ID NO:223), Rv1673c (SEQ ID NO:236), Rv3513c (SEQ ID NO:496), Rv3675 (SEQ ID NO:519), Rv3870 (SEQ ID NO:546), Rv3891c (SEQ ID NO:552), Rv0163 (SEQ ID NO:24), Rv0710 (SEQ ID NO:109), Rv1297 (SEQ ID NO:189), Rv1745c (SEQ ID NO:255), Rv0600c (SEQ ID NO:97), Rv1536 (SEQ ID NO:222), Rv1738 (SEQ ID NO:254), Rv2524c (SEQ ID NO:359), Rv3086 (SEQ ID NO:440), Rv3367 (SEQ ID NO:477), Rv0135c (SEQ ID NO:20), Rv0627 (SEQ ID NO:101), Rv1448c (SEQ ID NO:213), Rv3224a (SEQ ID NO:455), Rv0029 (SEQ ID NO:2), Rv0846c (SEQ ID NO:129), Rv1159 (SEQ ID NO:165), Rv1186c (SEQ ID NO:172), Rv1705c (SEQ ID NO:243), Rv1713 (SEQ ID NO:248), Rv2476c (SEQ ID NO:355), Rv3402c (SEQ ID NO:483), Rv2615c (SEQ ID NO:374), Rv2995c (SEQ ID NO:425), Rv3788 (SEQ ID NO:585), Rv0140 (SEQ ID NO:555), Rv0203 (SEQ ID NO:33), Rv1531 (SEQ ID NO:565), Rv1693 (SEQ ID NO:241), Rv1882c (SEQ ID NO:269), Rv2143 (SEQ ID NO:568), Rv2367c (SEQ ID NO:570), Rv0584 (SEQ ID NO:94), Rv1651c (SEQ ID NO:567), Rv3197a (SEQ ID NO:576), Rv3369 (SEQ ID NO:579), Rv3825c (SEQ ID NO:586), Rv0101 (SEQ ID NO:15), Rv0808 (SEQ ID NO:123), Rv0814c (SEQ ID NO:560), Rv2153c (SEQ ID NO:309), Rv2933 (SEQ ID NO:416), Rv0071 (SEQ ID NO:9), Rv2471 (SEQ ID NO:571), Rv2979c (SEQ ID NO:575), Rv0155 (SEQ ID NO:556), Rv0581 (SEQ ID NO:559), Rv2631 (SEQ ID NO:377), Rv3455c (SEQ ID NO:489), Rv3601c (SEQ ID NO:505), Rv0896 (SEQ ID NO:562), Rv1641 (SEQ ID NO:234), Rv3005c (SEQ ID NO:427), Rv3759c (SEQ ID NO:582), Rv3800c (SEQ ID NO:532), Rv0187 (SEQ ID NO:30), Rv2379c (SEQ ID NO:338), Rv2434c (SEQ ID NO:352), Rv2940c (SEQ ID NO:574), Rv3477 (SEQ ID NO:580), Rv0435c (SEQ ID NO:72), Rv0844c (SEQ ID NO:128), Rv0856 (SEQ ID NO:561), R 1191 (SEQ ID NO:564), Rv2803 (SEQ ID NO:397), Rv0783c (SEQ ID NO:118), Rv1054 (SEQ ID NO:563), Rv1689 (SEQ ID NO:240), Rv2539c (SEQ ID NO:572), Rv2859c (SEQ ID NO:573), Rv3777 (SEQ ID NO:528).

In additional methods, to identify serodiagnostic antigens, t-tests for each reactive antigen were performed comparing normalized signal intensities of TB-cases to controls, and exemplary results are shown in FIG. 2A. Here, Cyber T-tests revealed signals for 23 antigens as significantly different between the smear-positive TB cases (n=13) and the LTBI-negative controls (n=69). These antigens are shown in the histogram by the average of their normalized signal intensities for the two patient groups, and ranked in descending order of the signals in the smear-positive group. The p-value for each antigen is also shown (top), arranged so that the more significant antigens produce downward pointing spikes.

Based on probing sera from 48 LTBI-negative subjects and 50 TB culture positive subjects, a total of 31 antigens were found to discriminate between these groups and were considered serodiagnostic as depicted in FIG. 2B. It was further found that combining multiple antigens produces a test with increased specificity and sensitivity. The top 2 discriminatory antigens have an AUC of >0.88, and the addition of another 3 antigens to the classifier improves the AUC score to >0.90. Using 10 antigens gives an AUC score of >0.93. Remarkably, further addition of antigens does not improve the AUC score of the classifier. For the sera in this study the top 10 discriminatory antigens yields a sensitivity of >80% identification of true negatives and a sensitivity of >90% for finding the true positives. These results clearly support the ability of whole proteome chips using ORFeomes created using enzymeless recombination cloning, and proteomes expressed using E. coli based cell free expression systems, as valid tools for serodiagnostic antigen discovery. These classifiers will benefit from a larger, more comprehensive profiling study of well characterized serum samples.

The inventors then studied the diagnostic power of different numbers of ORFs using receiver operating characteristic (ROC) curves. A ROC curve is a parametric plot of the false positive rate (1—specificity) vs. the true positive rate (sensitivity) of a classifier as the underlying discrimination threshold is varied. The area under the curve (AUC) summarizes the results. An AUC of 1.0 indicates a perfect classifier, while an AUC of 0.51 (95% confidence interval, 0.43 to 0.59) is the expected value for a classifier that works by chance for the data set, as inferred by the method of Truchon and Bayly (J Chem Inf Model 47(2): 488-508). For multiple antigens, kernel methods and support vector machines were used (Bioinformatics: the Machine Learning Approach, Second Edition edn.: MIT Press) to build linear and nonlinear classifiers. As input to the classifier, the highest-ranking 1, 2, 5, 10, and 30, ORFs were used on the basis of either p-value or single antigen AUC and the results were validated with 10 runs of threefold cross-validation. The results (data not shown) showed that increasing the antigen number from 1 to 5, and from 5 to 10 produced an incremental improvement in the classifier. Increasing numbers beyond this did not improve the algorithm's ability to discriminate the two populations. Contingency tables built on these data showed that using 10 antigens at an optimal threshold provides an accuracy of 94% of the true positives and 78% of the true negatives.

Alternatively, antigen selection was also performed as follows: Raw data were distributed into the two groups of the query and subsets were normalized using vsn on the control spots. A CyberT test was run on the normalized data, and SVM classifier was built with a subset of the top antigens. Duplicates were removed. Each sample included meta data that was used to build each of the 10 queries, and each group was a disjoint subset of the original data, and each query only had two groups. Data were normalized using arsinh normalization (Bioinformatics, 18 Suppl 1, 2002), which compensates for variance dependence on mean. An affine-linear transformation (scale all value+add a value) was performed on each sample to compensate for shifts between samples, thus allowing a t-test on the normalized data. The CyberT test was used to estimate the variance of a spot by using neighboring spots (Bioinformatics, 17(6):509-519, 2001), giving a statistical measure of the difference in means between two groups for a particular antigen. Subsetting the p-values: Antigens are subset based on the significance of the p-value. Multiple test correction is used, and antigens are subset on the Bonferroni or the Benjamini-Hochberg p-value (<0.05) in most cases. Building a (SVM) classifier: Classifiers were built using a number of the top antigens to provide an estimate of what classification accuracy we could be obtained for each query. This allows for determination of the optimal number of antigens to be included in the final classifier. 3-fold cross-validation was used and ROC plots were generated to visualize the results. A list of exemplary results using this analysis is provided in the list of serodiagnostic antigens shown in FIG. 2C.

Enrichment analysis: To determine the features of proteins that were enriched in the immunodominant antigen set, proteins were classified into one of 11 functional categories according to the TubercuList genome database (http://genolist.pasteur.fr/TubercuList/). The number of ‘hits’ for each category was determined in the immunodominant antigen set. 7 immunodominant antigens were considered serodiagnostic, of which 4 (57.1%) were proteins with proline-glutamic (PE/PPE) motifs. Since the whole proteome contains 168 (4.2%) PE/PPE motif proteins, this represents a significant 13.6-fold enrichment relative to the whole proteome. Importantly, none of the 167 ‘cross-reactive’ immunodominant antigens were significantly enriched in any of the functional categories. The number of serodiagnostic antigens could be increased to 31 if all antigens were assessed regardless of immunodominance. Of these, 6 (19.4%) were virulence factors and 10 (32.2%) were PE/PPE motif proteins, representing a significant 7.7-fold enrichment for both, relative to the whole proteome. Interestingly, molecules involved in intermediary metabolism were significantly underrepresented (0.1-fold enrichment) in the serodiagnostic set relative to the whole proteome.

Several computational predictions were also made to classify the antigens. Lipoproteins and cell wall proteins were not enriched in the serodiagnostic antigen set, whereas possession of a signal sequence or an extracellular classification by PSORTb were enriching. High coil content, high glycine and high proline were all enriching features. PE/PPE molecules, characterized as having highly conserved proline rich motifs 100-200 amino acids long with high coil content near the N-terminus, were significant enriching features. Twenty-six out of 31 molecules in the serodiagnostic antigen set were negatively charged with isoelectric point <6.7. Again, none of these predicted features were enriched in the cross reactive antigen set.

Comparison of fluorescence and colorimetric detection of bound antibodies: The ability to replace fluorescence detection with a colorimetric methodology would assist in wider deployment of the arrays where fluorescence scanners would be impractical or where a smaller device would be preferable, such as in high containment laboratories or routine diagnostic laboratories. However, it was not known whether a colorimetric readout would have a reduced sensitivity or dynamic range compared to fluorescence. With this aim the HIS and HA tag-specific monoclonal antibodies were visualized with appropriate alkaline phosphatase-conjugated secondary antibodies and the arrays were developed with nitro-TB developer. Grey scale 2400 dpi resolution TIFF images were obtained using a conventional desktop document scanner and scatter plots of the 4608 data points compared with fluorescent detection. The correlation for signals for the HIS and HA tags were high (r2=0.8186 and 0.9259, respectively). Fluorescence based detection gave 99.2%, 97.0%, 96.6% and 0.4% for poly-His tag detection, HA tag detection, both tag detection and no tag detection, respectively. Colorimetric based detection gave 93.7%, 88.6%, 84.8% and 2.5% for poly-His tag detection, HA tag detection, both tag detection and no tag detection respectively. While fluorescence based detection is somewhat more sensitive (since there were fewer ‘double negatives’), alkaline phosphatase based detection is a comparable alternative that can be performed with only basic equipment. FIG. 3 depicts representative scans of arrays proved with antibodies to (A) HIS and (B) HA tag antibodies and visualized by fluorescence and colorimetric means; scatter plots are of colorimetric vs. fluorescence data.

Further illustrative exemplary methods and protocols are provided in the parent application PCT/US07/23299 (published as WO2008/140478), which is incorporated by reference herein.

Thus, specific embodiments and applications of compositions and methods related to antigens of M. tuberculosis have been disclosed. It should be apparent, however, to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Furthermore, where a definition or use of a term in a reference, which is incorporated by reference herein is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.

SEQUENCE LISTING

The Sequence Listing providing sequences with the SEQ ID NO:1 to SEQ ID NO:586 is submitted as a single file on a single compact disc in computer readable format, wherein the single file is entitled “101519.0003US1 Sequence listing_ST25.txt”, which was created May 8, 2009, which has a size of 948 kb, and which is incorporated by reference herein. 

What is claimed is:
 1. A method for detecting presence of antibodies which specifically bind to antigens of M. tuberculosis and which are present in a bodily fluid sample, comprising contacting the sample with antigens of M. tuberculosis, wherein at least two of the antigens are encoded by nucleic acids selected from the group consisting of Rv3804 (SEQ ID NO:534), and Rv2031 (SEQ ID NO:284), and detecting antibodies which bind to the antigens.
 2. The method of claim 1, wherein the antigens are present in a crude expression extract or in partially purified form.
 3. The method of claim 1, wherein the step of detecting the antibodies comprises use of a signal-generating anti-antibody.
 4. The method of claim 1, wherein binding affinity of respective antibodies which specifically bind to antigens of M. tuberculosis are known and indicative of an activity state of tuberculosis.
 5. The method of claim 1 wherein the antigens of M. tuberculosis are coupled to a solid phase prior to the step of contacting the sample with the antigens.
 6. The method of claim 5 wherein the antigens of M. tuberculosis are coupled to the solid phase in an array.
 7. The method of claim 1 further comprising a step of selecting the at least two of the antigens such that an average quantity of antibodies produced in a patient against the at least two antigens is in an upper quartile of quantity of antibodies produced in the patient.
 8. The method of claim 1 further comprising a step of selecting the at least two of the antigens on the basis of quantified and known relative reactivities with respect to sera of a population infected with M. tuberculosis.
 9. The method of claim 8 wherein the known reactivities are characterized by activity state of the disease.
 10. The method of claim 8 wherein the known reactivities are characterized by strength of immunogenicity.
 11. The method of claim 8 wherein the at least two of the antigens are immunodominant antigens.
 12. The method of claim 1 wherein the at least two of the antigens are known as being associated with active disease after infection.
 13. The method of claim 1 further comprising a step of detecting at least one additional antibody that specifically binds to an antigen of M. tuberculosis and that is present in the bodily fluid sample, wherein the antigen is encoded by a nucleic acid selected from the group consisting of Rv3864 (SEQ ID NO:545), Rv1980 (SEQ ID NO:281), Rv0632 (SEQ ID NO:103), Rv0456 (SEQ ID NO:74), Rv3810 (SEQ ID NO:536), Rv0379 (SEQ ID NO:65), Rv1837 (SEQ ID NO:264), Rv1886 (SEQ ID NO:270), Rv1196 (SEQ ID NO:174), Rv3248 (SEQ ID NO:458), Rv1837 (SEQ ID NO:264), Rv3628 (SEQ ID NO:513), Rv1284 (SEQ ID NO:187), and Rv1411c. 